The 3 roles AI agents play in your developer platform

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Engineering organizations are trying to deliver as fast as technology allows, bringing agentic AI into their developer platforms and working out how to use AI agents to maximize engineering productivity.

But when it comes to AI agents in an agentic developer platform, every team we talk with sees the role of those agents a little differently. Following hundreds of calls with our customers, we captured three types of roles.

Role 1: AI agents as platform consumers

In this role, an agent is basically a user of the platform. It uses the platform as part of its task to read context and to run actions. When agents first showed up, a lot of companies said they treat their AI agents like employees, and in a development platform that makes the agent just another engineering resource consuming it.

A typical case: an engineer asks Claude Code to add an endpoint to the payments service. Before it writes any code, the agent pulls the service owner, dependencies, and the standards it must meet from the platform, then spins up a preview environment via a self-service action and runs the tests.

“A lot of companies said they treat their AI agents like employees, and in a development platform that makes the agent just another engineering resource consuming it.”

For this to work, the agent has to reason over real, current information about your systems, starting with the service catalog and extending to ownership, dependencies, standards, and current state. If you get the context wrong, there’s a good chance an agent will get overconfident and do the wrong thing. Most teams solve this …

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